Skip to content

InitCond.md

Latest commit

 

History

History
82 lines (58 loc) · 6.67 KB

InitCond.md

File metadata and controls

82 lines (58 loc) · 6.67 KB
Raw

Back to Data pre-processing

Initial conditions

The InitCond module

The second step in the modeling run is the determination of the initial conditions for the following fits. This task is performed by a specific external module called InitCond. This can be launched by the corresponding function called InitCond():

import RTModel
rtm = RTModel.RTModel('/event001')
rtm.Reader()
rtm.InitCond()

With this code, we first perform the data pre-processing by Reader and then we set the initial conditions by InitCond. In the /event001 directory you will see that the following products appear:

  • In the subfolder ini/, the file InitCond.ini appears, which contains the current options with which InitCond has been launched.
  • A new subdirectory called InitCond/ is created. In this subdirectory there are several text files named InitCondXX.txt, with XX replaced by the label of the corresponding model category.
  • Each InitCondXX.txt contains the number of initial conditions and the parameters of each initial conditions line by line.
  • A file spline.txt in the base event folder containing the points of the spline models built by InitCond for each dataset.

After the execution of InitCond, you may call the run() function to complete the modeling run or the launch_fits() function for the fits you are interested in, as described in Fitting.

Setting initial conditions

In order to set initial conditions for modeling, InitCond executes the following steps:

  • Spline approximation of each dataset;
  • Identification of peaks in each datasets;
  • Removal of duplicate peaks;
  • Definition of initial conditions for single-lens models by using the main peak(s) and a grid search over the shape parameters;
  • Definition of initial conditions for binary-lens models by matching detected peaks to peaks of templates from a library;
  • Addition of old models from previous runs (if any).

The details of each step are illustrated in the RTModel paper.

Options for initial conditions

The config_InitCond() function

The user may specify his/her own options to drive the initial conditions to the desired result by calling the config_InitCond() function with the proper options:

import RTModel
rtm = RTModel.RTModel('/event001')
rtm.config_InitCond(npeaks = 2, peakthreshold = 10.0, oldmodels = 4, override = None,
                    nostatic = False, onlyorbital = False, usesatellite = 0, onlyupdate = False,
                    templatelibrary = None, modelcategories = ['PS','PX','BS','BO','LS','LX','LO']))
rtm.run()

The call to config_InitCond() will affect all following executions of the InitCond module, whether called through run() or InitCond(). If you want to change your options, you may call config_InitCond() again.

Description of the options

Here we describe the options for InitCond in detail indicating their default values.

  • peakthreshold = 10.0: Number of sigmas necessary for a deviation to be identified as a peak in a concave section with respect to a straight line joining the left and right boundaries of the section. A too low value will include noise in the baseline among peaks. A too high value will ignore small anomalies.
  • npeaks = 2: Number of peaks in the observed light curve to be considered for setting initial conditions. If you choose to use more than 2 peaks you will have many more fits to be run, with greater chances of success but longer computational time.
  • templatelibrary = None: Alternative user-defined template library file to be used to build initial conditions for binary-lens fits. You may learn more about the customization of template libraries in Template libraries.
  • override = None: If a t-uple is specified here (e.g (8760.1, 8793.1)), the elements of the t-uple are taken as peak positions in the data and directly used to define the initial conditions. The whole spline and peak identification procedure is then skipped.
  • usesatellite = 0: Initial conditions are set only considering peaks in the indicated satellite. If zero, ground datasets are used for initial conditions.
  • nostatic = False: If True, static models will not be calculated. This is useful if higher orders are significant and cannot be treated as a simple perturbation of static models. Furthermore, this option is recommended if you have observations from a satellite spaced by a distance of the order of au.
  • onlyorbital = False: If True, only orbital motion models will be calculated.
  • modelcategories = ['PS','PX','BS','BO','LS','LX','LO']: The list of model categories to be fit in this modeling run. For example rtm.config_InitCond(modelcategories = ['PS','PX','LS','LX','LO']) will exclude binary source models from fitting. Refer to Model categories for the meaning of all labels. Note that the additional model categories not fit by default (e.g. Keplerian orbital motion and triple lenses) can only be included through this option.
  • oldmodels = 4: If previous runs have been archived, the chosen number of best models from the last previous run are included as initial conditions. This can be useful for refining old models with new data or options.
  • onlyupdate = False: If True, the modeling run will be limited to a quick update of old models found in the last archived run as specified by the oldmodels option.

All options are also accessible separately as properties of the RTModel class. The user may thus modify the value of each option one by one. The names of the properties are the same as the options in config_InitCond() with the prefix InitCond_, as shown in the example below:

rtm.InitCond_peakthreshold = 20.0
rtm.InitCond_nostatic = True

An empty call to config_InitCond() with no parameters will reset all variables to the default values. Notice that the options that are not explicitly specified in the call to config_InitCond() are always reset to their default values. This is also true if you previously used the recover_options() function to inherit the options from a previous run (see Archiving and updating).

Recording the options

In each modeling run, the options for InitCond are stored in the file InitCond.ini in the /ini subdirectory within the event directory for later reference. If the modeling run is archived, also the whole /ini subdirectory is saved so that the user may check the options used in each modeling run. The function recover_options() can be used to load the options from a previous run.

Go to Fitting